Lead, Financial Crime Data & Analytics (AML)

Bendigobank; Sydney; Hybrid; AUD 180,000 - 240,000; Full time

Benefits offered by this job

Hybrid work model

Health insurance support

BEN U access

EAP for you and family

Job summary

Bendigo Bank is seeking a Manager, FCFO Data & Analytics (AML) to lead our Financial Crime & Fraud Operations analytics team in Melbourne, with flexible hybrid work across Australia. You will translate regulatory requirements into high-performing surveillance models, tune detection rules, and deliver data-driven insights to risk leadership while mentoring a team of analytics professionals.

This role collaborates across risk, investigations, technology, data, and external vendors to uplift

Qualifications

• Proven leadership of analytics professionals in financial services.
• Deep AML/CTF and sanctions expertise.
• Hands-on experience with enterprise monitoring platforms such as NetReveal.
• Proficiency with SQL, Python, GCP, and data visualization tools.
• Strong communication with executive and risk stakeholders.
• Knowledge of AUSTRAC obligations and governance.

Responsibilities

• Lead a high-performing analytics team of financial crime professionals.
• Oversee detection systems tuning across AML monitoring and screening.
• Support regulatory reporting governance including SMRs and TTRs.
• Develop data-driven risk dashboards and operational reporting.
• Collaborate with risk, investigations, tech, data, and vendors to calibrate rules.
• Drive analytics transformation via platform upgrades and data pipelines.

Skills

Analytical Leadership

AML/CTF Expertise

Surveillance Systems

SQL

Python

GCP

Data Visualization

Stakeholder Mgmt

AUSTRAC Knowledge

Education

Data Analytics Degree

ACAMS

AFCS

Tools

NetReveal

Job description

Bendigo Bank is seeking a Manager, FCFO Data & Analytics (AML) to lead our Financial Crime & Fraud Operations analytics team in Melbourne, with flexible hybrid work across Australia. You will translate regulatory requirements into high-performing surveillance models, tune detection rules, and deliver data-driven insights to risk leadership while mentoring a team of analytics professionals.

This role collaborates across risk, investigations, technology, data, and external vendors to uplift